DJ-1 modulates the unfolded protein response and cell death via upregulation of ATF4 following ER stress
Bibliographic record
Abstract
Abstract The unfolded protein response (UPR) triggered by endoplasmic reticulum (ER) stress is a feature of many neurodegenerative diseases including Alzheimer’s disease, Huntington’s disease and Parkinson’s disease (PD). Although the vast majority of PD is sporadic, mutations in a number of genes including PARK7 which encodes the protein DJ-1 have been linked to early-onset, familial PD. In this regard, both PD of sporadic and genetic origins exhibit markers of ER stress-induced UPR. However, the relationship between pathogenic mutations in PARK7 and ER stress-induced UPR in PD pathogenesis remains unclear. In most contexts, DJ-1 has been shown to protect against neuronal injury. However, we find that DJ-1 deficiency ameliorates death in the context of acute ER stress in vitro and in vivo. DJ-1 loss decreases protein and transcript levels of ATF4, a transcription factor critical to the ER response and reduces the levels of CHOP and BiP, its downstream effectors. The converse is observed with DJ-1 over-expression. Importantly, we find that over-expression of wild-type and PD-associated mutant form of PARK7 L166P , enhances ER stress-induced neuronal death by regulating ATF4 transcription and translation. Our results demonstrate a previously unreported role for wild-type and mutant DJ-1 in the regulation of UPR and provides a potential link to PD pathogenesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".